GMO North America | Europe | Asia-Pacific Ten Lessons (Not?) Learnt - - PowerPoint PPT Presentation

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North America | Europe | Asia-Pacific

Ten Lessons (Not?) Learnt Asset Allocation

James Montier

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Lesson I: Markets aren’t efficient

A long litany of bad ideas: CAPM Alpha and Beta Black and Scholes Risk management Mark-to market M&M dividend and capital structure irrelevance Shareholder Value Regulatory regime Most insidious aspects of EMH are the advice on sources of outperformance Inside information (illegal in most places) If you can see the future better than everyone else Also tells us that opportunities will be fleeting

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Not a drop of evidence that we can forecast anything at all

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1 2 3 4 5 6 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Economist forecast Actual result

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Forecast error over time: US and European markets 2001-2006, %

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Analyst expected returns (via target prices) and actual returns (US, %)

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10 20 30 40 50 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Analysts’ forecast Actual outturn

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10 20 30 40 50 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Analysts’ forecast Actual outturn

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Lesson II: Relative Performance is a dangerous game

Homo Ovinus

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Institutional investors vs. US market (weight difference)

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1 2 3 4 5 Small Large Value Growth High Momo Low Momo High Accruals Low Accruals High issue Low issue

Source: Lewellen (2009)

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Many active managers aren’t even trying!

Lewellen concludes: “Quite simply, institutions overall seem to do little more than hold the market

• portfolio. Their aggregate portfolio almost perfectly mimics the value-weighted

index... Institutions overall take essentially no bet on any of the most important stock characteristics known to predict returns, like B/M, momentum, or accruals. The implication is that, to the extent that institutions’ holdings deviate from the market portfolio, they seem to bet primarily on idiosyncratic returns – bets that aren’t particularly successful. Another implication is that institutions, in aggregate, don’t exploit anomalies in the way they should.”

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Why not? Career and Business risk (Homo Ovinus rides again)

Cohen et al ‘Best Ideas’

2 4 6 8 1 0 1 2 1 4 1 6 1 8 2 0 B e s t Id e a s M a r k e t

Cohen et al conclude “The poor overall performance of mutual fund managers… is not due to a lack

• f stock-picking ability, but rather to

institutional factors that encourage them to

• verdiversify.”

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Performance around hiring and firing decisions (%)

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Lesson III: This time is never different

0.5 1 1.5 2 2.5 3 3.5 1 12 23 34 45 56 67 78 89 100 111 122 M

• nths

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Mill/Minsky/Kindleberger framework for bubbles Displacement Credit Creation Euphoria Critical Stage/Financial Distress Revulsion

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Why don’t we see bubbles?

Black Swans – Unpredictable – Massive Impact – Ex-post rationalization Predictable Surprise – At least some where aware of the problem – The problem gets worse over time – Eventually explodes into crisis Five impediments to recognising predictable surprises: (i) Over-optimism (ii) The illusion of control (iii) Self-serving bias (iv) Myopia (v) Inattentional blindness

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Lesson IV: Valuation Matters (in the long run)

Source: GMO

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Buy when it’s cheap: if not then, when?

Buying at 10x G&D PE

12 4

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Average 6 4

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1982.03 3 1

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1942.03 21 8

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1931.10 18 3

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1917.09

US market 1881-2008

100 100 100 100 100 85 242 125 102 131 87 243 126 112 134 5 100 100 100 100 83 8 18 5 15

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82 93 52 41 34 9 95 100 90 92 82

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3

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93 80 43 37 26 10 92 94 91 92 80

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• 26
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101 67 41 34 21 13

10 Yr 5 Yr 3 Yr 2 Yr 1 Yr 10 Yr 5 Yr 3 Yr 2 Yr 1 Yr 10 Yr 5 Yr 3 Yr 2 Yr 1 Yr

Source: GMO

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Graham and Dodd PE (S&P500)

10 20 30 40 50 60 1881 1885 1890 1894 1899 1903 1908 1913 1917 1922 1926 1931 1936 1940 1945 1949 1954 1958 1963 1968 1972 1977 1981 1986 1991 1995 2000 2004 2009

Source: GMO

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Bottom up valuation: What would Ben think?

5 10 15 20 25 UK Europe US Japan Asia Now Mar-09 Nov-08 % of stocks passing BG conditions

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Lesson V: Wait for the “fat pitch”

100 200 300 400 500 600 1 2 3 4 5 6 7 8 9 10 11 12

Source: Plottt et al

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ADHD and stock holding periods

Source: NYSE

1 2 3 4 5 6 7 8 9 10 1920 1925 1930 1935 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005

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Lesson VI: Sentiment matters

Source: GMO

2 4 6 8 10 12 Low PE High PE

Low Sentiment High Sentiment

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Exploiting sentiment (US 1962-2000)

Source: Baker and Wurgler

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0.5 1 1.5 2 Age (old vs young) Volatility (high vs low) Profitability (high vs low)

Sentiment Low Sentiment High When sentiment is low: Buy young, volatile, unprofitable firms When sentiment is high: Buy old, stable, profitable firms

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Sentiment suggests need for caution

96 97 98 99 00 01 02 03 04 05 06 07 08 09 15 20 25 30 35 40 45 50 55 ADVISORS SENTIMENT BEARISH

Source: DATASTREAM

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Lesson VII: Leverage can’t turn a bad investment good

• Leverage can’t turn a bad investment good, but it can turn a

good one bad

• Limits staying power
• Can turn a temporary impairment (i.e. price volatility) into a

permanent impairment of capital

• Beware of financial innovation…often just leverage in a thinly

veiled disguise

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Lesson VIII: Beware of over-quantification

Ben Graham: “Mathematics is ordinarily considered as producing precise and dependable results; but in the stock market the more elaborate and abstruse the mathematics the more uncertain and speculative are the conclusions we draw there from…Whenever calculus is brought in, or higher algebra, you could take it as a warning that the operator was trying to substitute theory for experience, and usually also to give to speculation the deceptive guise of investment.” Keynes: “With a free hand to choose coefficients and time lag, one can, with enough industry, always cook a formula to fit moderately well a limited range of past facts. I think it all hocus - but everyone else is greatly impressed, it seems, by such a mess of unintelligible figures.” Munger: “It seems like higher mathematics with false precision should help you, but it doesn’t. They teach that in business schools because, well, they’ve got to do something!” There are no points for elegance in the real world.

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Risk isn’t a number

Risk isn’t volatility, it is the permanent impairment of capital Volatility creates the opportunity. Keynes again: “It is largely fluctuations which throw up the bargains and the uncertainty due to fluctuations which prevents other people from taking advantage of them.” Think about risk as a trinity: Valuation risk Business risk Financing risk

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Lesson IX: There is no substitute for skepticism

Santayana: “Skepticism is the chastity of the intellect, and it is shameful to surrender it too soon or to the first comer: there is nobility in preserving it coolly and proudly.” We are in the rejection game.

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Lesson X: Benefits of cheap insurance

Insurance is often disliked in investing, because of the nature of the cash flows, but that often makes it cheap! Examples: Inflation insurance Moral hazard/market melt up insurance

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Long-term volatility

5 15 25 35 45 55 65 75 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79 82 85 88 91 94 97 00 03 06 09

Source: SG, Bloomberg

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Lessons (not) learnt

I. Markets aren’t efficient II. Relative performance is a fool’s game III. This time is never different

• IV. Valuation matters

V. Wait for the fat pitch

• VI. Sentiment matters
• VII. Leverage can’t make a bad investment good
• VIII. Beware of over-quantification
• IX. There is no substitute for skepticism

X. Don’t underestimate the use of cheap insurance

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